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Edge-based local adaptive thresholding system and methods for foreground detection

机译:基于边缘的局部自适应阈值系统和前景检测方法

摘要

Systems and methods for generating a locally adaptive threshold image for foreground detection performing operations including creating a saliency edge strength image or layer indicating edge or border pixels of the nuclei by performing tensor voting on pixels neighboring the initial edge pixels within an image region to refine true edges are featured. Further, for each of a plurality of regions or blocks of the image, an adaptive threshold image is determined by sampling a foreground pixel and a background pixel for each initial edge pixel or refined edge pixel, generating histograms for both background and foreground saliency (or gradient magnitude) modulated histograms, determining a threshold range for each block of the image, and interpolating the threshold at each pixel based on the threshold range at each block. Comparing the input image with the resulting locally adaptive threshold image enables extraction of significantly improved foreground.
机译:用于生成用于前景检测的局部自适应阈值图像的系统和方法,其执行以下操作:包括通过对图像区域内与初始边缘像素相邻的像素执行张量投票,来创建表示核的边缘或边界像素的显着性边缘强度图像或层,以显示出真实的边缘特征。此外,对于图像的多个区域或块中的每个,通过对每个初始边缘像素或精炼边缘像素采样前景像素和背景像素,生成背景和前景显着度的直方图,确定自适应阈值图像(或梯度幅度)调制直方图,确定图像每个块的阈值范围,并根据每个块的阈值范围对每个像素的阈值进行插值。将输入图像与得到的局部自适应阈值图像进行比较,可以提取前景明显改善的图像。

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